Algorithm Online Training

Needintech's Online Algorithm Course help you develop your ability to articulate problem-solving processes and to efficiently implement those processes within software. You'll learn how to create algorithms for searching, sorting, and optimization and then apply them to real-world problems.

Algorithms Course Description

Algorithms for numerical, string, and geometric operations such as polynomial multiplication, matrix operations, GCD, pattern matching, subsequences, sweep, and convex hull are covered as the course proceeds. The graph algorithms shortest path and spanning tree serve as its conclusion.

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Needintech's mock interviews provide a platform for you to prepare for, practise for, and experience a real-life job interview. You will have an advantage over your colleagues if you familiarise yourself with the interview environment beforehand in a comfortable and stress-free environment.

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Course Objetives
  • A step-by-step procedure used to solve a problem or accomplish a goal is known as an algorithm. It’s a straightforward idea; for common activities like deciding whether to drive or take the train to work or figuring out what you need from the grocery store, you apply your own algorithms.
  • Understanding and applying algorithmic problem-solving techniques is a crucial skill for solving complex computing problems, and studying this field necessitates more specialised prerequisites than some programming-focused computer science courses.
  • Because algorithms are central to so many different types of computer programming work, professionals with this skill set can end up working in high-paying positions in a variety of companies. Experience with algorithms, for example, is required for work as a data scientist, one of the most in-demand jobs in technology.
  • If you understand the fundamentals of computer science and how they apply to algorithmic processing, you may be able to determine whether algorithms are right for you. These fundamentals would include knowledge of computer architecture, data structures, math, and logic. These areas may yield insights into arrays, linked lists, binary trees, set theory, and linear equations.
  • Algorithm-related topics to research include logistic regression, neural networks, data mining, automated financial trading, artificial intelligence, and quantum computing. These could be in addition to other heavy topics like deep learning, mathematical equations, and statistics. Knowing these can help you understand how algorithms and computers interact.
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Syllabus of Algorithms Online Course

Module 1 : Preliminaries

  • Introduction to algorithms
  • Asymptotic notation
  • Logarithms and more



Module 2: Data Structures

  • Elementary data structures
  • Dictionary data structures

Module 3: Sorting

  • Applications of Sorting
  • Heapsort/Priority Queues
  • Mergesort/Quicksort
  • Linear sorting

Module 4 : Graph Algorithms

  • Data structures for graphs
  • Breadth-first search
  • Topological sort/connectivity
  • Minimum spanning trees
  • Shortest paths
  • Exploiting graph algorithms

Module 5 : Search

  • Combinatorial search
  • Program optimization

Module 6 : Decomposition

  • Elements of dynamic programming
  • Examples of dynamic programming

Module 7 : Spring Break

  • Limitations of dynamic prog

Module 8 : Intractability

  • Reductions
  • Easy reductions
  • Harder reductions
  • The NP-completeness challenge
  • Approximation Algorithms
  • Heuristic methods

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